Known methods for analyzing the image contents of a test body are mainly based on metrics for determining similarities, such as distance measurements of segmented objects, or the calculation of global threshold distributions. These methods are based on translatorily invariable initial spectra. Situations often occur in reality, such as object displacements underneath the recording system, or different backgrounds during recording, or aliasing effects, so that in many cases a direct comparison of these initial spectra cannot be performed.
It is known from the reference book of Thomas TILLI, “Mustererkennung mit Fuzzy-Logik: Analysieren, klassifizieren, erkennen und diagnostizieren” [Pattern Recognition by Means of Fuzzy Logic: Analyzing, Classifying, Determining and Diagnosing], Franzis-Verlag GmbH, München, publishers, 1993, pp. 183/184, 208 to 210, 235 to 257, to use fuzzy logic for image processing, wherein a spectral transformation can be one type of signal preparation.
The technical article “Mustererkennung mit Fuzzy-Logik” [Pattern Recognition by Means of Fuzzy Logic] by Peter ARNEMANN, Elektronik 22/1992, pages 88 to 92, describes how to perform pattern recognition by the use of fuzzy logic.
The article by D. Charalampidis, T. Kasparis, M. Georgiopoulos, J. Rolland “A Fuzzy ARTMAP-Based Classification Technique of Natural Textures”, Fuzzy Information Processing Society, 1999, NAFIPS, 18th International Conference of the North American Fuzzy Information Processing Society, Jun. 10 to 12 1999, pp. 507 to 511, describes the performance of pattern recognition with a training phase and the use of a window of 16×16 pixels for image recognition.
The publication “Volker Lohweg and Dietmar Müller: Ein generalisiertes Verfahren zur Berechnung von translationsinvarianten Zirkulartransformationen für die Anwendung in der Signal-und Bildverarbeitung” [A Generalized Method for Calculating Translation-invariant Circular Transformations for Employment in Signal and Image Processing], Mustererkennung [Pattern Recognition] 2000, 22nd DAGM Symposium, 09/13 to 15/2000, pages 213 to 220” describes the mathematical bases and the application of circular transformation in image processing.
USP 0,039,446/2002 discloses a method for comparing two patterns by the use of classification methods.